I specialize in optimizing Federated Learning for wireless edge networks. My research addresses critical energy and latency bottlenecks, highlighted by the development of the “FedBDC” framework which significantly reduces power consumption for IoT devices. Moving forward, I aim to bridge the gap between theoretical algorithms and practical applications, expanding into fields like Smart Agriculture. My vision is to become a global innovator, delivering sustainable, cross-disciplinary AI solutions to solve real-world societal challenges.